code: def xyz_to_rgb(image: torch.Tensor) -> torch.Tensor:
      r"""Convert a XYZ image to RGB.
  
      Args:
          image: XYZ Image to be converted to RGB with shape :math:`(*, 3, H, W)`.
  
      Returns:
          RGB version of the image with shape :math:`(*, 3, H, W)`.
  
      Example:
          >>> input = torch.rand(2, 3, 4, 5)
          >>> output = xyz_to_rgb(input)  # 2x3x4x5
      """
      if not isinstance(image, torch.Tensor):
          raise TypeError(
              f"Input type is not a torch.Tensor. Got {type(image)}"
          )
  
      if len(image.shape) < 3 or image.shape[-3] != 3:
          raise ValueError(
              f"Input size must have a shape of (*, 3, H, W). Got {image.shape}"
          )
  
      x: torch.Tensor = image[..., 0, :, :]
      y: torch.Tensor = image[..., 1, :, :]
      z: torch.Tensor = image[..., 2, :, :]
  
      r: torch.Tensor = (
          3.2404813432005266 * x
          + -1.5371515162713185 * y
          + -0.4985363261688878 * z
      )
      g: torch.Tensor = (
          -0.9692549499965682 * x
          + 1.8759900014898907 * y
          + 0.0415559265582928 * z
      )
      b: torch.Tensor = (
          0.0556466391351772 * x
          + -0.2040413383665112 * y
          + 1.0573110696453443 * z
      )
  
      out: torch.Tensor = torch.stack([r, g, b], dim=-3)
  
      return out
  
file_path: kornia/kornia/color/xyz.py
imports: import torch
  from torch import nn
label_desc: Use image node_id 2 for calling a global function with example usage: xyz_to_rgb(image) and returns: out